IBM and Stream Computing

Normally I do not write about vendor products but since today’s topic seems to be a new driver for the industry, I will make an exception. Today’s topic is about IBM Infosphere Streams product which introduces a new term to our industry: Stream Computing.

Stream Computing concept stems from the fact that todays’ OSS/BSS environment is composed of “streams” of data flowing between the systems. Each stream serve different purposes. The stream that fetches CDR data to the mediation system over the ftp protocol serves to the Order to Cash process. Another stream that looksup the segment information of a given MSISDN from the
Campaing Management Application could serve to a different end-to-end process.

Stream computing allows us to “intercept” and do additional actions over the traditional streams that we use in our operations.

Take mediation example: We fetched the CDR from the switch to the mediation system. This is a standard ftp operation and until it finalizes no system has a control over its payload. If we put a stream computing system between these two, we can intercept the data and play with the payload. Here is how it works:

You create the main stream in the Infosphere Streams system, which does the real thing: ftp, from one place to the other. This operation is transparent to the OSS systems in the chain: The mediation system “thinks” that it is getting the data from switch. And since we do not “touch” this main stream, there’s little or no latency in the mediation process.

The magic, however, lies within the Infosphere Streams. With this product you can “clone” the stream to serve parallel different purpose. Following the same example, I clone the main stream and I have two output data now: CDR information. The second stream, goes to another OSS system which checks the MSISDN with the campaign mgmt system to see if this is a VIP activity. If so, the VIP customer can be SMSed after the call for example.

Streams reaches billions of events per second in the data processing speeds, which can easily cope with Telecom’s moving data speed and volume.

As you may know, IBM is spending too much time for the research an development of AI systems. AI studies go in parallel with big data studies. The most recent outcome of these studies was the introduction of Watson, which is an AI program equipped with big data processing algorithms.

It will be wise to combine stream computing with these AI study outcomes and IBM seems to be moving in that direction.